scholarly journals The Degree of Polymerization in a Prediction Model of Insulating Paper and the Remaining Life of Power Transformers

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 670
Author(s):  
Sherif S. M. Ghoneim
Keyword(s):  
Mathematical Model ◽  
Degree Of Polymerization ◽  
Power Transformers ◽  
Remaining Life ◽  
Dissolved Gases ◽  
Statistical Tools ◽  
Insulating Paper ◽  
Tan Δ ◽  
Insulation Status ◽  
Oil Color

The aging of power transformers causes several defects and damages in the insulating system, especially in the insulating paper. The degradation of the insulating paper generates dissolved gases in the insulating oil, which are measured by gas chromatography and used as an indicator of the insulation status. The state of the insulating paper can be identified based on the degree of polymerization (DP) measurement. In some cases, when the measurement of DP is difficult, estimating DP can be accomplished through gathering information about some of the testing parameters, such as the dissolved gases (DGA), breakdown voltage (BDV), oil interfacial tension (IF), oil acidity (ACI), moisture content (MC), oil color (OC), dielectric loss (Tan δ), and furans concentration specifically (2-furfuraldhyde (FA)). The statistical tools (correlation and multiple linear regression), based on 131 transformer samples, can be used to build a relation linking DP and one or more of the previous parameters to identify the insulating paper status and the percentage of remaining life of the transformer. The results indicated that it is difficult to build a mathematical model to relate between the DP and the testing variables, except with FA, where the trend of DP with FA is more obvious than with other variables. The empirical formula to compute DP based on the FA concentration was developed and gave promising results to compute DP and the remaining life of the power transformers.

scholarly journals Quantitative Analysis of Ageing Condition of Insulating Paper Using Infrared Spectroscopy

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
R. Saldivar-Guerrero ◽  
E. N. Cabrera Álvarez ◽  
U. Leon-Silva ◽  
F. A. Lopez-Gonzalez ◽  
F. Delgado Arroyo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Quantitative Analysis ◽  
Empirical Model ◽  
Diagnostic Technique ◽  
Degree Of Polymerization ◽  
Economic Losses ◽  
Remaining Life ◽  
Life Estimation ◽  
Insulating Paper ◽  
Ageing Condition

Transformers are very expensive apparatuses and are vital to make the whole power system run normally. The failures in such apparatuses could leave them out of service, causing severe economic losses. The life of a transformer can be effectively determined by the life of the insulating paper. In the present work, we show an alternative diagnostic technique to determine the ageing condition of transformer paper by the use of FTIR spectroscopy and an empirical model. This method has the advantage of using a microsample that could be extracted from the transformer on-site. The proposed technique offers an approximation quantitative evaluation of the degree of polymerization of dielectric papers and could be used for transformer diagnosis and remaining life estimation.

scholarly journals Determination of Transformers’ Insulating Paper State Based on Classification Techniques

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 427 ◽  
Author(s):  
Sherif S. M. Ghoneim
Keyword(s):  
Prediction Model ◽  
Power Flow ◽  
Degree Of Polymerization ◽  
Classification Techniques ◽  
Aging Rate ◽  
Insulating Oil ◽  
Insulating Paper ◽  
Key Indicator ◽  
Carbon Dioxide Co2

The continuity of transformer operation is very necessary for utilities to maintain a continuity of power flow in networks and achieve a desired revenue. Most failures in a transformer are due to the degradation of the insulating system, which consists of insulating oil and paper. The degree of polymerization (DP) is a key detector of insulating paper state. Most research in the literature has computed the DP as a function of furan compounds, especially 2-furfuraldehyde (2-FAL). In this research, a prediction model was constructed based on some of most periodical tests that were conducted on transformer insulating oil, which were used as predictors of the insulating paper state. The tests evaluated carbon monoxide (CO), carbon dioxide (CO2), breakdown voltage (VBD), interfacial tension (IF), acidity (ACY), moisture (M), oil color (OC), and 2-furfuraldehyde (2-FAL). The DP, which was used as the key indicator for the paper state, was categorized into five classes labeled 1, 2, 3, 4, and 5 to express the insulating paper normal aging rate, accelerating aging rate, excessive aging danger zone, high risk of failure, and the end of expected life, respectively. The classification techniques were applied to the collected data samples to construct a prediction model for the insulating paper state, and the results revealed that the fine tree was the best classifier of the data samples, with a 96.2% prediction accuracy.

Combined Implementation of Dynamic Rating-based Protection and Calculating the Average Degree of Polymerization for Power Transformers

2021 ◽  
Vol 141 (7) ◽  
pp. 528-534
Author(s):  
Kohei Ito ◽  
Mutsumi Aoki ◽  
Toru Amau ◽  
Tetsuo Otani ◽  
Tatsuya Ozawa ◽  
...  
Keyword(s):  
Degree Of Polymerization ◽  
Average Degree ◽  
Power Transformers

Oil health index calculation and incipient fault diagnosis in power transformers using fuzzy logic

2022 ◽  
Vol 64 (1) ◽  
pp. 28-37
Author(s):  
T Manoj ◽  
C Ranga
Keyword(s):  
Fuzzy Logic ◽  
Logic Model ◽  
Transformer Oil ◽  
Power Transformers ◽  
Dissolved Gases ◽  
Health Index ◽  
Fuzzy Logic Model ◽  
Proposed Model ◽  
Incipient Faults ◽  
Incipient Fault

In this paper, a new fuzzy logic (FL) model is proposed for assessing the health status of power transformers. In addition, the detection of incipient faults is achieved where two or more faults exist simultaneously. The process is carried out by integrating a fuzzy logic model with the conventional International Electric Committee (IEC) ratio codes method. As transformer oil insulation deteriorates, excess percentages of dissolved gases such as hydrogen, methane, ethane, acetylene and ethylene are induced within the trasnformer. The status of oil health is generally assessed using these gas concentrations. Therefore, in the proposed model, 31 fuzzy rules are designed based on the severity levels of these gases in order to determine the health index (HI) of the oil. Similarly, any incipient faults along with their severity are also detected using the proposed fuzzy logic model with 22 expert rules. To validate the proposed fuzzy logic model, the data for dissolved gases in 50 working transformers operated by the Himachal Pradesh State Electricity Board (HPSEB), India, are collected. Over the years, calculations for the health index have been performed using conventional dissolved gas analysis (DGA) interpretation methods. The shortcomings of these methods, such as non-reliability and inaccuracy, are successfully overcome using the proposed model. The detection of incipient faults is normally performed using key gas, Rogers ratios, the Duval triangle, Dornenburg ratios, modified Rogers ratios and the IEC ratio codes methods. The shortcomings of these conventional ratio code methods in identifying incipient faults in some typical cases, ie multiple incipient fault cases, are overcome by the proposed fuzzy logic model.

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